As is known, the efficiency of many critical systems used, for example, in aircraft, trains, motor vehicles, nuclear plants, biomedical equipment, etc., depends on sophisticated graphic human-machine interfaces (HMIs) of digital display systems. To improve the efficiency of HMIs and make them easier to use, increasingly complex, flexible, high-power digital display systems have been devised over the past few years, thus resulting in an enormous increase in the amount of testing required to ensure an adequate degree of dependability, and which may run to as many as hundreds of thousands of tests.
At present, many electronic systems are tested on computer-aided test benches programmed to simulate the system's operating environment, and automatically real-time or offline test system performance to detect any malfunctions.
Despite the advantages of bench testing, only digital display system input/output signals are currently tested automatically, while, using scripts to set system operating scenarios, the display performance of digital display systems is still mostly tested by human operators monitoring the system's screen.
Human-operator testing display performance is seriously complicated when dealing with leading-edge systems, in which digital display systems are graphic servers designed to execute high-level graphic commands and receive numerous commands simultaneously from different client computers. Systems of this sort call for testing both individual digital display systems and computers, as well as operation of the integrated system as a whole, which, as stated, may involve testing hundreds of thousands of graphic images.
In recent years, to automate display performance testing of digital display systems, it has been proposed to take pictures of digital display system screens using digital cameras, and compare the pictures with reference images to reveal any display anomalies. Testing this way, however, has proved unsatisfactory, owing to the wide tolerance range of currently used digital camera sensors, which are also affected by surrounding light and result in a high percentage of spurious errors.
Moreover, in recent years, some automatic test systems for analogical video signals have been also proposed. In particular, said proposed automatic test systems are based on digital acquisition of analogical video signals, for example based on analogical frame grabbing. Moreover, most of said automatic test systems perform quality analyses of digitally-acquired, analogical video signals under test, and/or analyses, direct or indirect, of differences of digitally-acquired, analogical video signals under tests and reference video signals.
In this connection, EP1727376 discloses a real-time video quality measurement instrument. In particular, according to EP1727376, a signature of a digitally-acquired, analogical video signal under test is computed and used, along with a pre-stored signature computed for a reference digitally-acquired, analogical video signal, to spatially and temporally align the video signal under test with the reference video signal. Video quality measurements are then performed on the aligned frames of the digitally-acquired, analogical video signal under test and the digitally-acquired, reference analogical video signal.
Furthermore, US2005071108 discloses a method and an apparatus for automated testing of display signals from video graphics circuitry. In particular, the method according to US2005071108 includes: capturing analogical display signals that are provided from a processing device to a display device; converting the analogical display signals into data acquisition signals (where a data acquisition signal includes a converted display signal having the display information contained therein); and providing the data acquisition signals to a test system that tests the analogical display signals.
Additionally, CN101594551 discloses an image display testing method, which comprises the following steps: connecting an electronic device to be tested and a computer system; sending an instruction of image play to the electronic device to be tested by the computer system; responding to the instruction, executing an image auto-play program, and simultaneously outputting a digital image signal by the electronic device to be tested; acquiring the digital image signal, reducing the digital image signal into an image, and carrying out pixel comparative analysis on the image and a sample image by the computer system; if the comparative analysis result is in an allowable error range, making the image test pass, and ending the test process; while, if the comparative analysis result exceeds the allowable error range, selecting whether to restart the test by repeating the test steps, or to end the test process.
Moreover, JP2118689 discloses an automatic inspecting device for analogical Cathode-Ray Tube (CRT) signals. In particular, according to JP2118689, the analogical CRT signals of one picture are completely input into the automatic inspecting device and signature data of the analogical CRT signals is generated by a signature producing circuit and then fetched into a controller, in which the fetched signature data is compared with previously stored expected data to decide their normal or defective condition. The decided result is output through an interface. Whether the analogical CRT signals are right or wrong is decided with all pictures to be inspected until the reading of a counter reaches the number of picture to be inspected. Thereby, the automatic inspection of the CRT interface which outputs the analogical CRT signals is possible.
Lastly, WO2007022250 discloses display device ON/OFF detection methods and apparatus. In particular, a method according to WO2007022250 for determining whether a presentation device is ON or OFF comprises: determining a plurality of metrics based on monitoring at least one output of the presentation device, wherein each metric in the plurality of metrics comprises a decision indicating an operating state of the presentation device; and combining the plurality of metrics to determine whether the presentation device is ON or OFF, wherein combining the plurality of metrics comprises at least one of weighting the plurality of metrics or determining a majority vote of the plurality of metrics.